1. Field of the Invention
This invention relates to velocity estimation using Doppler techniques, and more particularly to a spatial vector averaging method and apparatus for estimating blood flow velocities in a medical diagnostic apparatus using ultrasonic pulse signals.
2. Background of the Invention
Medical diagnostic ultrasound apparatus generate images of anatomical structures within a body of a patient by transmitting ultrahigh-frequency sound waves (typically on the order of 3.0 MHz) into the patient and then analyzing the echoes, i.e., ultrasonic signals reflected from the structure of the body being scanned. Perhaps the most widely used ultrasound diagnostic apparatus displays in real-time anatomical information in the form of a two-dimensional image of a selected cross-section of the structure. The ultrasound signals are swept across the structure in the form of a sector scan. The sector scan is performed in real-time so that the image is available during the examination of the patient. In such cases, motion of the structure produces a corresponding moving image (i.e., a B-mode image).
In some clinical applications, e.g., cardiac imaging, anatomical defects can be relatively small and beyond the resolution capabilities of conventional anatomical ultrasound imaging. However, since a small anatomical defect may manifest itself by a pronounced change in blood flow velocity, for example aortic stenosis, mitral or aortic insufficiency or a congenital defect, a display of blood flow velocity would allow these abnormalities to be more easily detected. One known method for velocity display is to use FFT techniques to process the echo signals reflected from a selected small volume so as to generate a numerical display. This method is severely limited by the fact that velocity is only determined for the small sample volume and is also not a two dimensional real-time image. Real-time imaging of velocity in a larger area is highly desireable. Thus, velocity blood flow imaging has become an increasingly important portion of the ultrasound imaging device used in the medical diagnostic field, wherein a real-time blood flow image is superimposed over a real-time anatomical image. However, it is difficult to acquire sufficient ultrasound data to develop an accurate and high resolution blood flow image which can be displayed in real-time at a sufficiently high rate. This is because many echos need to be processed in a short time while the physical reality is that ultrasound signals have a relatively slow propagation speed in a human body, thereby limiting the number of echoes which can be received in a short time.
European Patent Publication No. 0 100 094 by Namekawa of the Aloka Company describes an ultrasound blood flow imaging apparatus for two-dimensional display i.e., mapping, of blood flow velocities within a body. The flow mapping is superimposed over a B-mode scan and displays blood flow in a color which is representative of the direction of the blood flow with respect to the ultrasonic transducer while variations in the intensity of the colors are representative of the blood flow velocities. It is only noted therein that the blood flow velocity signal is generated using a pulsed-Doppler method.
Present Dopper velocity estimators use time-domain processing techniques wherein a series of N repetitive pulses of RF-ultrasonic signal separated by time periods of T are transmitted towards a moving target along a given scan direction. A relatively large number of echo signals (from a minimum of 10 to a maximum of 256) are processed using Doppler techniques for determining the velocity and turbulence of the moving object. One such technique for determining Doppler frequency shift is shown, for example, by U.S. Pat. No. 4,542,657 issued to Barber et al. which uses I and Q sampled signals of a plurality (i.e., from 16 to 256) of the demodulated echo signals. FFT and zero-crossing velocity estimators are described in U.S. Pat. No. 4,318,413 for processing the Doppler signal. Another time-domain processing technique uses autocorrelaton (pulse-pair) algorithms, such as known, for example, from an article by Kasai et al. published in the IEEE Transactions on Sonics and Ultrasonics, Volume SU-32, No. 3, May 1985. Each of the above time-domain processing techniques evaluate a relatively large number of return echoes (from 10 to 256) for estimating blood flow velocity and turbulence.
For a better understanding of the time-domain processing technique and its relation to the present invention, reference is now made to FIG. 1a herein, which shows groups (or pulses) of ultrasonic signal 1, 2, 3, . . . n which are excited and groups of return echo signals e.sub.1, e.sub.2, e.sub.3 . . . e.sub.n which are received in response thereto. The echoes are reflections from a target (i.e., blood) moving along a scan line A in a direction toward the ultrasonic transducer. FIG. 1b illustrates a rearrangement of six groups of the return echoes, wherein the t axis represents the axial depth or spatial direction and the tau axis represents the temporal direction. T represents the time delay, typically 200 microseconds, between the start of successive ultrasonic pulse transmissions. Note that the time shift between successive ones of the echoes is substantially uniform due to the relatively short time period between pulses as compared with the velocity of the moving target.
The autocorrelation method, which is generally recognized to provide superior performance for real-time blood flow imaging than the other known techniques, will be briefly described in conjunction with FIG. 1b. The autocorrelation type of time domain processing can be represented by the following equations:
For simplicity of formulations, we consider reflected echoes from a single target to be represented by EQU Z(t) =a(t) cos [w.sub.0 t+.phi.(t)] (1)
where a(t) is the ultrasonic signal pulse envelope, w.sub.0 is the carrier frequency, and .phi.(t) is the phase response. When the target moves by a time shift .alpha.T during a pulse repetition period T, Eq. 1 for the n-th echo becomes EQU Z.sub.n (t)=a(t-.alpha.nT) cos [w.sub.0 (t-.alpha.nT)+.phi.(t-.alpha.nT)](2)
where .alpha. is the Doppler ratio given by .alpha.=w.sub.d /w.sub.0 and w.sub.d is the Doppler frequency.
After quadrature demodulation, the demodulated signal e.sub.n (t) of Eq. (2) can be written as ##EQU1##
In Eq. (3), a(t) is mostly determined by the impulse response of the ultrasound transducer. For multiple targets having the same velocity, Eq. (3) is valid. However, the phase response of a(t) will include interference from multiple targets. If the multiple targets have different velocities, Eq. (3) will not be valid. However, we can approximate this situation by considering a(t) as a broadband signal which has several frequency components. Consequently, our aim in flow imaging is to estimate mean and variance of the frequency spectrum of the demodulated signal given by Eq. (3).
In the known autocorrelation processing method, each echo signal vector e.sub.n is multiplied in the axial direction by the complex conjugate of the adjacent echo signal vector e.sub.n-1, which results in a plurality of pulse-pair vector signals e.sub.1 *e.sub.2, e.sub.2 *e.sub.3, e.sub.3 *e.sub.4, . . . e.sub.n e.sub.n-1 *. The amplitude of the resulting N-1 pulse-pair signals, at a certain axial depth represented by the Doppler time axis (the dashed line in FIG. 1b) are then averaged in the temporal (tau) direction.
The autocorrelation can be represented by two steps of pulse-pair vector calculation and averaging. ##EQU2## where N is the number of temporal averagings. The phase of the pulse-pair vector in Eq. (4) represents instantaneous frequency of the input Doppler signal which is changing from pulse to pulse. The temporal averaging of Eq. (5) provides averaged vectors from which we can find a mean frequency.
From the amplitude and phase of the resultant averaged vectors, the mean frequency, which corresponds with the velocity of the blood, can be obtained. Furthermore, the variance (sigma squared) of the velocity can be obtained, which corresponds to the turbulence of the blood flow. Turbulence estimations also provide useful diagnostic information when displayed. The phase (velocity) and variance are calculated as follows: ##EQU3## wherein R(T) is an abbreviated notation of R(T; nT, t) and R(T)=R.sub.r (T)+jR.sub.i (T)
For further details concerning this pulse-pair autocorrelation technique, the reader is referred to the forenoted article by Kasai et al.
Known autocorrelation velocity processing techniques suffer from the following two problems. Firstly, it is desirable that blood flow mapping have information updated on the order of 24-30 frames/second for best diagnostic effectiveness. Since existing autocorrelation techniques use temporal averaging, as exemplified by equations 1-7, averaging of a plurality (n) of received echo vectors is required. Thus, it is required to wait for the receipt of a plurality of echoes before an accurate analysis of the Doppler signal can be made. This results in a relatively low frame rate i.e., in the order of 15 frames/second. If less echoes were used the frame rate could be increased, however the accuracy of the velocity estimation would be severely degraded. Furthermore, since turbulence is in effect a differentiation of velocity with respect to time, due to amplitude fluctuations of the velocity signal, the receipt of even more echoes is required in order to arrive at an accurate turbulence estimation. The second problem results from the fact that the period of the amplitude and phase variations of the Doppler signal (the Doppler signal being the signal amplitude variations along a Doppler axis, such as shown in FIG. 1c) depends upon the blood flow velocity. In slower flows, the time shift between adjacent echoes is reduced. As can be easily visualized in FIG. 1a and 1b, this causes the period of the Doppler signal to become longer. Consequently, a greater number of echoes are required to be processed for accurate estimation of a slower velocity. In the known ultrasound systems employing velocity estimation, the number of received echoes which are averaged is decided by the maximum flow velocity (and is at least seven echo signals) so as to obtain accurate blood flow velocity mapping at about 15 frames/second. However, even more echo signals are required to be processed to develope an accurate blood flow map which includes slower velocities, thereby reducing the frame rate even more.
It is an object of the present invention to provide a Doppler blood flow velocity and turbulence estimator which minimizes the number of received echoes required for accurate estimation of blood flow velocity and turbulence in order that an accurate color blood flow mapping can be provided at a relatively high frame rate, for example 24 or 30 frames/second.